Automatic Multilevel Thresholding Based on a Fuzzy Entropy Measure

Histogram Thresholding is an image processing technique whose aim is that of separating the objects and the background of the image into non overlapping regions. In gray scale images this task is obtained by properly detecting, on the corresponding gray levels histogram, the valleys that space out the concentration of the pixels around the characteristic gray levels of the different image structures. In this paper, a novel procedure will be discussed exploiting fuzzy set theory and fuzzy entropy to find automatically the optimal number of thresholds and their location in the image histograms.